a Create a 4 period moving average forecast, an exponential smoothing forecast with alpha 0 2, and a linear trend forecast for your data b Calculate the MSE and MAD for each c Plot the original series, and each of the forecasts d Create forecasts for 2014 using each of these three techniques If you had to choose one of these, which would you choose and why e Given your data, and this time period, would you prefer to try some other type of forecast, or modify the data in some way Area State 2004Q1 30047652 2004Q2 30728148 2004Q3 31022260 2004Q4 31945284 2005Q1 31513672 2005Q2 31944216 2005Q3 32342544 2005Q4 34026564 2006Q1 34175320 2006Q2 34765912 2006Q3 34925760 2006Q4 34819512 2007Q1 35327056 2007Q2 35862472 2007Q3 35806612 2007Q4 36073896 2008Q1 36487704 2008Q2 36884104 2008Q3 36681284 2008Q4 36633932 2009Q1 36374664 2009Q2 36356632 2009Q3 36410864 2009Q4 36534624 2010Q1 35967844 2010Q2 36632768 2010Q3 37381300 2010Q4 37848672 2011Q1 38536956 2011Q2 38532632 2011Q3 39238020 2011Q4 39182704 2012Q1 39808460 2012Q2 40540924 2012Q3 40191504 2012Q4 41689684 2013Q1 40999499 2013Q2 41855162 2013Q3 41934431 2013Q4 42184911 Include instructions on how to plug this into excel

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Question: a. Create a 4-period moving average forecast, an exponential smoothing forecast with alpha=0.2, and a linear trend forecast for your data. b. Calculate the MSE

a. Create a 4-period moving average forecast, an exponential smoothing forecast with alpha=0.2, and a linear trend forecast for your data.
b. Calculate the MSE and MAD for each.
c. Plot the original series, and each of the forecasts.
d. Create forecasts for 2014 using each of these three techniques. If you had to choose one of these, which would you choose and why?
e. Given your data, and this time period, would you prefer to try some other type of forecast, or modify the data in some way?

Area	State
2004Q1	30047652
2004Q2	30728148
2004Q3	31022260
2004Q4	31945284
2005Q1	31513672
2005Q2	31944216
2005Q3	32342544
2005Q4	34026564
2006Q1	34175320
2006Q2	34765912
2006Q3	34925760
2006Q4	34819512
2007Q1	35327056
2007Q2	35862472
2007Q3	35806612
2007Q4	36073896
2008Q1	36487704
2008Q2	36884104
2008Q3	36681284
2008Q4	36633932
2009Q1	36374664
2009Q2	36356632
2009Q3	36410864
2009Q4	36534624
2010Q1	35967844
2010Q2	36632768
2010Q3	37381300
2010Q4	37848672
2011Q1	38536956
2011Q2	38532632
2011Q3	39238020
2011Q4	39182704
2012Q1	39808460
2012Q2	40540924
2012Q3	40191504
2012Q4	41689684
2013Q1	40999499
2013Q2	41855162
2013Q3	41934431
2013Q4	42184911

Include instructions on how to plug this into excel.

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